Linear regression analysis investigating the association between personality traits and sleep quality, as measured by PSQI global score.

<p>N = 1,406</p><p><i>Note</i>. All models were adjusted for age, marital status, smoking, and working status.</p><p>^a Model I: linear regression model including a single domain of personality as an independent variable (R2 = 0.043, 0.023, 0.020, 0.026, and 0.027; adjusted R² = 0.040, 0.020, 0.016, 0.022, and 0.023, <i>F</i> = 12.67, 6.70, 5.61, 7.45, and 7.68; <i>P</i><.001, <i><</i>.001, <0.001, <i><</i>.001, and <0.001 in N, E, O, A, and C, respectively).</p><p>^b Model II: multiple linear regression model including all five domains of personality as independent variables (R² = 0.0524, adjusted R² = 0.041, <i>F</i> = 4.80, <i>P</i><.001).</p><p>^c β: standardized coefficient in linear regression analyses.</p><p>^d Unique = proportion of criterion variance explained uniquely by the predictor.</p><p>^e Common = proportion of criterion variance explained by the predictor that is also explained by one or more other predictors. Unique + Common = <i>r</i>², <i>r</i> = zero-order correlation coefficient</p><p>*<i>p</i> <.05</p><p>**<i>p</i> <.01</p><p>***<i>p</i><.001</p><p>Linear regression analysis investigating the association between personality traits and sleep quality, as measured by PSQI global score.